Adding features and changing structures are two entirely different things.

Most recent service introductions feature terms like "AI-based," "AI-applied," and "AI-embedded." However, many services simply add AI functionality to existing structures, essentially equating them to services with AI. Conversely, some services are designed with AI in mind from the planning stage, with their structure and flow designed with AI in mind. These two approaches are fundamentally different, both technically and business-wise. Failure to distinguish this distinction can lead to overestimating the benefits of AI adoption or, conversely, missing out on essential competitive advantages.

What are AI-powered services?

AI-enabled services maintain the existing service structure and user flow while adding AI to specific functions. In this case, AI functions as a supplementary function rather than a core component. The characteristics of AI-enabled services are as follows.

• Automate or supplement some of the existing functions without replacing them.
• The service works the same even without AI.
• The center of user experience is still in the existing UI/flow.

For example, adding recommendation algorithms to search functions or introducing chatbots to customer service centers are examples of such approaches. While these approaches offer the advantages of rapid adoption and low risk, they are unlikely to alter the fundamental competitiveness of a service.

What are AI-designed services?

An AI-designed service is one that is designed from the planning stage to incorporate AI as a core premise. In this case, AI is not a function, but rather is embedded in the very operation of the service. The characteristics of an AI-designed service are as follows:

• User input and behavior become the main material for AI judgment.
• The service flow is not fixed and changes fluidly depending on the situation.
• The result may not be a predefined screen, but rather a response generated or assembled by AI.

In these services, data structures, model design, and feedback loops play a more important role than the UI. AI is not an option, but rather a prerequisite for the service's success.

Differences from a structural perspective

1. Service-centric vs. AI-centric

Services with AI are centered around the service structure, with AI serving as a tool to support that structure. Conversely, services designed with AI are centered around AI judgment, and the service structure is more like an interface for conveying that judgment.

2. Fixed flow vs. dynamic flow

Existing services are designed to force users to follow a set path. AI-powered services also maintain this flow. In contrast, services designed with AI can have varying flow patterns depending on the user's context, and even the same input can produce different results.

Differences in user experience (UX)

Services that incorporate AI can recognize when users are using AI features. Functions like recommendations, summaries, and automated responses are clearly defined. In contrast, services designed with AI prioritize the experience of naturally delivering results over the mere fact that users are using AI. Rather than being prominently displayed, AI permeates the entire service.

Differences from a technical and operational perspective

1. Data dependency

AI-powered services can operate to a limited extent even with insufficient data. However, without data, AI-designed services struggle not only with performance but also with the service itself. Data collection, refinement, and feedback structures become essential.

2. Operational complexity

Services that incorporate AI don't require significant changes to existing operating systems. Conversely, services designed with AI require ongoing operational intervention, such as model performance management, prompt design, and data quality management. This isn't technical debt; it's part of the service itself.

Differences from a business perspective

1. Depth of differentiation

While AI-powered services offer a short-term competitive advantage in functional competition, their differentiation quickly erodes when competitors introduce similar features. Conversely, AI-designed services, due to their inherently different structure, are more expensive to imitate and more likely to maintain long-term competitiveness.

2. Scalability and directionality

Services that incorporate AI tend to reinforce existing business models. Services designed with AI have the potential to create new business models or even change the very definition of service.

Which choice is better?

It's impossible to definitively say which service is superior, AI-embedded or AI-designed. What matters is the purpose and the stage. If your goal is short-term efficiency improvements and rapid experimentation, an AI-embedded approach might be appropriate. However, if you prioritize AI as the core competitive edge of your service and aim for long-term change, an AI-designed approach is necessary.

Insight Summary

Services incorporating AI are closer to functional expansion, while services designed with AI are closer to structural transformation. The former is fast and secure, but has clear limitations, while the latter is complex and risky, but brings about significant change. The starting point for AI strategy is not the question of "whether to use AI," but rather defining the position AI should occupy within the service. When this distinction is clear, AI becomes a real competitive advantage, not just a marketing slogan.